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Identifying influential multinomial observations by perturbation

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  • Nyangoma, S.O.
  • Fung, W.-K.
  • Jansen, R.C.

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  • Nyangoma, S.O. & Fung, W.-K. & Jansen, R.C., 2006. "Identifying influential multinomial observations by perturbation," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2799-2821, June.
    • Handle: RePEc:eee:csdana:v:50:y:2006:i:10:p:2799-2821
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    References listed on IDEAS

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    1. D. A. Williams, 1987. "Generalized Linear Model Diagnostics Using the Deviance and Single Case Deletions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(2), pages 181-191, June.
    2. Lee, A. J. & Nyangoma, S. O. & Seber, G. A. F., 2002. "Confidence regions for multinomial parameters," Computational Statistics & Data Analysis, Elsevier, vol. 39(3), pages 329-342, May.
    3. Wing K. Fung & C. W. Kwan, 1997. "A Note on Local Influence Based on Normal Curvature," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(4), pages 839-843.
    4. Fung, Wing-Kam, 1992. "Some diagnostic measures in discriminant analysis," Statistics & Probability Letters, Elsevier, vol. 13(4), pages 279-285, March.
    5. Lee, Sik-Yum & Xu, Liang, 2004. "Influence analyses of nonlinear mixed-effects models," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 321-341, March.
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    Cited by:

    1. Alejandra Tapia & Victor Leiva & Maria del Pilar Diaz & Viviana Giampaoli, 2019. "Influence diagnostics in mixed effects logistic regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 920-942, September.

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